Team situational awareness in the context of hospital emergency: A concept analysis DOI
Modi Al‐Moteri

International Emergency Nursing, Journal Year: 2023, Volume and Issue: 69, P. 101284 - 101284

Published: May 31, 2023

Language: Английский

Wind dynamic and energy-efficiency path planning for unmanned aerial vehicles in the lower-level airspace and urban air mobility context DOI
Y.Y. Chan, Kam K.H. Ng,

C.K.M. Lee

et al.

Sustainable Energy Technologies and Assessments, Journal Year: 2023, Volume and Issue: 57, P. 103202 - 103202

Published: April 7, 2023

Language: Английский

Citations

10

Structural safety evaluation using Bayesian ensemble neural networks DOI

Jin-Ling Zheng,

Sheng-En Fang

Engineering Structures, Journal Year: 2025, Volume and Issue: 328, P. 119709 - 119709

Published: Jan. 21, 2025

Language: Английский

Citations

0

A multi-aircraft co-operative trajectory planning model under dynamic thunderstorm cells using decentralized deep reinforcement learning DOI
Bizhao Pang, Xinting Hu, Mingcheng Zhang

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103157 - 103157

Published: Feb. 3, 2025

Language: Английский

Citations

0

Gaze behaviours, situation awareness and cognitive workload of air traffic controllers in radar screen monitoring tasks with varying task complexity DOI
Cho Yin Yiu, Kam K.H. Ng, Qinbiao Li

et al.

International Journal of Occupational Safety and Ergonomics, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Feb. 11, 2025

Objectives. Air traffic controllers should maintain high situational awareness (SA) and low cognitive workload to ensure aviation safety. However, increased task complexity may influence air controllers' SA workload. Meanwhile, eye-tracking provides insights into the gaze patterns that might signify SA. This article investigates behaviours, of different radar screen monitoring tasks with varying complexity. Methods. Twenty-eight participants performed three tasks, including call-sign association, position identification heading projection. Cognitive were evaluated for each using National Aeronautics Space Administration load index (NASA-TLX) global assessment technique (SAGAT), respectively. The Gaussian mixture model was used cluster high/low. Eye-tracking reveals behaviours contribute formation. Results. significantly differ between levels While has a significant main effect on fixations human operators, it does not pupil diameter. Conclusions. Fixation-related metrics changes in under complexity, while side effects be mitigated.

Language: Английский

Citations

0

A study of dynamic functional connectivity changes in flight trainees based on a triple network model DOI Creative Commons
Ye Lü,

Liya Ba,

Dongfeng Yan

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 6, 2025

The time-varying functional connectivity of the Central Executive Network (CEN), Default Mode (DMN), and Salience (SN) in flight trainees during a resting state was investigated using dynamic network (dFNC). study included 39 37 age- sex-matched healthy controls. Resting-state fMRI data behavioral test outcomes were obtained from both groups. Independent component analysis (ICA), sliding window, K-means clustering approaches utilized for evaluating (FNC) temporal metrics based on triple networks. Correlation analyses performed assessments these metrics. demonstrated significantly enhanced connection linking CEN DMN 2 (P < 0.05, FDR corrected). Additionally, spent less time 5, while they exhibited protracted mean dwell fractional windows 2, which correlated with accuracy Berg Card Sorting Test (BCST) Change Detection (all P 0.05). improved between following completion rigorous training resulted increased stability. This enhancement may be relevant to cognitive abilities such as decision-making, memory, information integration. When multitasking, displayed superior visual processing skills flexibility. dFNC research provides unique perspective sophisticated capabilities that are required high-demand, high-stress occupations piloting, thereby providing significant insights into intricate brain mechanisms inherent domains.

Language: Английский

Citations

0

A human-centric model for task demand assessment based on unsupervised learning-assisted eye movement measure DOI
Bufan Liu, Sun Woh Lye,

Kai Xiang Yeo

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103259 - 103259

Published: March 14, 2025

Language: Английский

Citations

0

Towards trustworthy civil aviation hazards identification: An uncertainty-aware deep learning framework DOI

Zhaoguo Hou,

Huawei Wang,

Minglan Xiong

et al.

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103280 - 103280

Published: March 29, 2025

Language: Английский

Citations

0

Effects of time interval and request modality on driver takeover responses: Identifying the optimal time interval for two-stage warning system DOI
Jie Zhang, Zhi Zhang, Tingru Zhang

et al.

Accident Analysis & Prevention, Journal Year: 2025, Volume and Issue: 215, P. 108008 - 108008

Published: March 30, 2025

Language: Английский

Citations

0

Sustaining aviation workforce after the pandemic: Evidence from Hong Kong aviation students toward skills, specialised training, and career prospects through a mixed-method approach DOI Open Access
Cho Yin Yiu, Kam K.H. Ng, S. C. M. Yu

et al.

Transport Policy, Journal Year: 2022, Volume and Issue: 128, P. 179 - 192

Published: Sept. 20, 2022

Language: Английский

Citations

15

Improved air traffic flow prediction in terminal areas using a multimodal spatial–temporal network for weather-aware (MST-WA) model DOI
Yang Zeng, Minghua Hu, Haiyan Chen

et al.

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 62, P. 102935 - 102935

Published: Oct. 1, 2024

Language: Английский

Citations

3